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DigitalGlobe“™s Tony Frazier: Govt Leaders Recognize Need to Leverage Machine Learning, Big Data Analytics

DigitalGlobe“™s Tony Frazier: Govt Leaders Recognize Need to Leverage Machine Learning, Big Data Analytics - top government contractors - best government contracting event
Tony Frazier
DigitalGlobe“™s Tony Frazier: Govt Leaders Recognize Need to Leverage Machine Learning, Big Data Analytics - top government contractors - best government contracting event
Tony Frazier

Tony Frazier, senior vice president of government solutions at DigitalGlobe, has said the U.S. government acknowledges the need to leverage big data analytics, machine learning, automation and other commercial technology platforms in order to help transform the intelligence community and global mapping efforts.

Frazier wrote in a blog post published Friday that government leaders such as Robert Cardillo, director of the National Geospatial-Intelligence Agency; and Lt. Gen. Vincent Stewart, head of the Defense Intelligence Agency; discussed the opportunities and potential challenges associated with the increasing adoption of sensors and new data sources at the GEOINT 2017 Symposium.

Cardillo, an inductee into Executive Mosaic“™s Wash100 for 2017, spoke about Beachfront and NSG Open Mapping Enclave projects at the U.S.  Geospatial Intelligence Foundation-sponsored event and how such efforts help NGA extract data from satellite imagery, Frazier noted.

Beachfront works to produce automated shoreline data through the use of various imagery sources, while NOME is a crowdsourcing-based mapping tool designed to help NGA clients derive points of interest such as buildings and roads from satellite imagery and facilitate data sharing in cloud environments.

Frazier said analysts and developers at DigitalGlobe and its newly acquired business The Radiant Group support such projects.

He added that Cardillo also expressed his goal to automate up to 75 percent of repetitive tasks in order to direct analysts“™ attention towards pattern discovery and synthesis efforts.

“For this vision to become reality, our customers need to train effective algorithms to automatically recognize objects and activity; create scalable methods to enrich, store and index all of this data spatially and temporally; and develop analytic modeling tools able to reveal patterns by processing massive amounts of data,“ Frazier wrote.

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